Customers receive their blank checks from a payor (financial) institution. A payor institution is thus a paying financial institution on whose account a check is drawn and by whom it is paid.
Check clearing is the process of reconciling payments among parties associated with a check-based financial transaction. Most checks are processed in the following manner: The entity to whom the check is made out (the payee) deposits the check in his or her bank (the bank of first deposit or the depository bank). If the checkwriter's (the payor) account is in the same bank, the check is “on-us” and it is processed at the bank. Otherwise, the physical check travels, often via a financial intermediary, to the payor's institution or bank (the paying financial institution or bank), and finally to the payor, who receives the canceled checks and/or an account statement of the canceled checks on a periodic basis, typically monthly. The checks that must travel (interbank transit checks) may be handled by multiple institutions. If the payor has insufficient funds in his or her account to clear the check, or if the paying financial institution does not honor the check for other reasons, the check travels back to the bank of first deposit and possibly back to the payee. The payee suffers a payment loss on checks that do not clear.
The figures in the present specification illustrate both the prior art and the present invention depict “paper check processing.” However, there are other financial instruments, such as debit cards, electronic checks (echecks), and Automated Clearing House (ACH) debit system transactions, which are ultimately tied into the checking account of a payor institution, and thus are functionally equivalent to paper checks. For simplicity, both the prior art descriptions and the present invention collectively refer to all of these types of financial instruments as “checks.”
FIG. 1 shows examples of three conventional channels of check activity for use of the customer's checks. In one channel, a customer presents a check to a merchant to buy a product or service. The merchant, in turn, deposits the check into a “bank of first deposit,” also known as the “depository bank.” In a second channel, a customer deposits a check directly into a bank of first deposit (the check may or may not be drawn on the bank of first deposit). In a third channel, the customer makes a payment to a payment processor. Like the merchant, the payment processor, in turn, deposits the check into a bank of first deposit. The bank of first deposit sends all checks (other than its own) to be cleared to the Federal Reserve and/or directly to the payor institution (e.g., payor bank).
FIG. 1 of U.S. Pat. No. 5,175,682 (Higashiyama et al.) and the corresponding description on column 1 of this patent provides a general overview of one conventional check clearing process for the merchant channel discussed above. In FIG. 1, the merchant bank 103 is the bank of first deposit, and the issuing bank 106 is the payor institution that issued the customer a checking account on which check 101 is drawn.
A “return item” is a check that is returned unpaid by the paying (payor) institution to the bank of first deposit, usually for insufficient funds. These bounced checks are reported back to the bank of first deposit in a “returns file.” FIG. 2 of the present specification illustrates FIG. 1 of U.S. Pat. No. 5,175,682 appended to show returns being sent by the issuing bank 106 to the merchant bank 103. A similar flow of returns occur in FIG. 1 of the present specification. (Return items that flow out of the payor institution are referred to as “outgoing returns,” whereas return items that are received by a bank of first deposit are referred to as “incoming returns.”)
FIGS. 1 and 2 of the present specification also shows a prior art check risk decision process associated with a risk assessment service. A merchant, bank of first deposit, or payment processor may subscribe to a service that assesses the risk that a check will be returned on an account based on checking account status and item level data provided by the payor institution. This may be done immediately or in an overnight batch process.
The risk assessment service maintains a single “participant database” 10 (shown in separate blocks in FIG. 1 for each channel for ease of illustration) which is populated on a daily basis with the checking account status and item level data of accounts at certain payor institutions (i.e., the participants) that belong to a member service or member network. FIG. 2 also shows the role of the participant database 10.
FIG. 3 shows that the prior art participant database 10 is populated by a daily flow of checking account status and item level data from each of the participant payor institutions. Some examples of a checking account status data are provided below (meaning of the status is noted in parenthesis where needed for a full understanding):                PRESENT (balance is greater than zero)        NEW ACCOUNT        CLOSED        NSF STATUS (balance is less than zero)        
Some examples of item level data are provided below:                STOP PAYMENTS        EARLY OUTGOING RETURN NOTICES        
Depending upon the information in the participant database 10, along with other pieces of key information such as the depositor's current balance, number of returns, past experience, a depository bank or institution may place an extended hold on the deposit if there is reason to doubt collectability. In the payment world, a payment processor may use this information to make a decision regarding whether or not to open the line of credit or “open to buy” until the check clears. A merchant may also use the information to decline to accept the check. The participant database is a highly reliable source of data because it is populated with actual checking account status and item level data received directly from the payor institutions. Accordingly, merchants, banks of first deposit, and payment processors can make accurate check risk decisions (e.g., check acceptance decisions and check hold decisions). Primary Payment Systems, Inc. (PPS), Scottsdale, Ariz., provides advance notice of potential check returns to inquiring customers using the participant database described herein.
One significant deficiency with the conventional schemes described above is that not all payor institutions belong to (i.e., are members of) the risk assessment service that maintains the participant database, and thus not all checking accounts have checking account status and item level data present in the participant database. If a check is presented from an account of a non-participating payor institution, then the merchant, bank of first deposit, or payment processor must rely on other sources of data to make a check risk decision, such as calling the payor institution directly, using other check verification services that obtain data from other sources, or reviewing past check history records for the customer that is presenting the check or the account that the check is drawn on. Entities that accept checks, and which already use services such as those provided by PPS, would like to rely upon a better and more accurate source of data when determining the likelihood that a check from a specific checking account that is not in the participant database will be returned so that better and more accurate check risk decisions can be made.
Check verification services currently used by merchants, banks and the like in making check acceptance decisions have many deficiencies. Some of the deficiencies are discussed below:
1. Services that use “negative file” databases which contain checking account numbers that are known to be closed or delinquent are typically based on return experiences from selected merchants, and thus are limited in scope and may become stale or outdated.
2. Retail merchants, financial institutions, check cashing services, check printing companies, collection agencies, and government agencies routinely report incoming returns (e.g., bounced checks), closed accounts, new check orders, and the like to private services, who, in turn, use this information in developing proprietary databases such as negative files for check verification. However, the vast majority of checking account activity data consists of checks that clear with no problems. The proprietary databases either do not capture such activity data, or they capture it from sources that are limited in scope (e.g., selected merchants as described in the previous paragraph). Incoming return data has much better meaning when combined with transit items which include therein checks that will ultimately clear with no problem. Consider, for example, a checking account holder who writes 100 checks in one year, averaging $40.00, but then accidentally bounces one $15.00 check during the course of the year. Many existing check verification services will flag the account as a problem account due to the bounced check, when, in fact, the likelihood of a check clearing on the account is extremely high.
3. Some check verification services use predictive models based on multiple variables to determine the level of risk associated with a particular check transaction. However, the predictive models may not take into account actual check activity behavior of the check presenting customer. Thus, a customer who has a stellar check activity record might fit a profile of a bad check writer and be negatively treated as a result of the profile which may not even factor in actual check activity. U.S. Pat. No. 5,679,938 (Templeton et al.) describes the use of a typical predictive modeling system.
4. Conventional check verification databases that are built from retailer (merchant) check activity data inherently miss a large percentage of checking accounts that are rarely, if ever, used for consumer-type purchases. Furthermore, a large percentage of retailers do not subscribe to, or report check activity to, a check acceptance service, and thus the databases do not contain a complete picture of the checkwriting activity of the checking accounts that even make it into the databases. Positive files (positive databases), negative files (negative databases) and velocity/risk databases, which are typically created by check acceptance services used by retailers, suffer from these deficiencies. Even the largest commercially available services today have no checking account activity data on about half or more of active checking accounts.
Despite the multitude of existing check verification and acceptance services, there is still an unmet need for a service that can be used to make statistically significant check risk decisions based at least in part on actual checking account activity data for a greater percentage of active checking accounts, and which can be used with confidence by merchants, banks and payment processors alike. The present invention fulfills such a need.